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Record W4412491235 · doi:10.1126/science.ado2403

Polyglycine-mediated aggregation of FAM98B disrupts tRNA processing in GGC repeat disorders

2025· article· en· W4412491235 on OpenAlexaff
Jason Yang, Yunhan Xu, David R. Ziehr, Martin S. Taylor, Max L. Valenstein, Evgeni M. Frenkel, Jack R. Bush, Kate Rutter, Igor Stevanovski, Charlie Y. Shi, Maheswaran Kesavan, Ricardo Mouro Pinto, Ira W. Deveson, David P. Bartel, David M. Sabatini, Raghu R. Chivukula

Bibliographic record

VenueScience · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversité Laval
FundersNational Institute of Neurological Disorders and StrokeNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesNational Institute on AgingNational Institutes of Health
KeywordsTransfer RNARNA splicingGlycineProteomeRNA-binding proteinChemistryBiologyBiochemistryCell biologyGeneticsRNAAmino acidGene

Abstract

fetched live from OpenAlex

Aggregation-prone polyglycine-containing proteins produced from expanded GGC repeats are implicated in an emerging family of neurodegenerative disorders. In this study, we showed that polyglycine itself forms aggregates that incorporate endogenous glycine-rich proteins, including FAM98B, a component of the transfer RNA (tRNA) ligase complex (tRNA-LC) that harbors the most glycine-rich sequence in the human proteome. Through this glycine-rich intrinsically disordered region (IDR), polyglycine sequesters and depletes the tRNA-LC, disrupting tRNA processing. Accordingly, patient tissues revealed aggregate-associated FAM98B depletion and accumulation of aberrant tRNA splicing intermediates. Furthermore, Fam98b depletion in adult mice caused progressive motor coordination deficits and hindbrain pathology. Our data suggest that the FAM98B glycine-rich IDR mechanistically links previously disparate neurodegenerative disorders of protein aggregation and tRNA processing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.170

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.281
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2025
Admission routes1
Has abstractyes

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